Research Article
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Year 2023, , 176 - 183, 27.06.2023
https://doi.org/10.54287/gujsa.1276486

Abstract

References

  • Azli, T., & Chaoui, Z. E.-A. (2015). Performance revaluation of a N-type coaxial HPGe detector with front edges crystal using MCNPX. Applied Radiation and Isotopes, 97, 106-112. doi:10.1016/j.apradiso.2014.12.027
  • Cebastien Joel, G. S., Maurice, N. M., Eric Jilbert, N. M., Ousmanou, M., & David, S. (2018). Monte Carlo method for gamma spectrometry based on GEANT4 toolkit: Efficiency calibration of BE6530 detector. Journal of Environmental Radioactivity, 189, 109-119. doi:10.1016/j.jenvrad.2018.03.015
  • Díaz, N. C., & Vargas, M. J. (2010). Improving the trade-off between simulation time and accuracy in efficiency calibrations with the code DETEFF. Applied Radiation and Isotopes, 68(7-8), 1413-1417. doi:10.1016/j.apradiso.2009.11.021
  • Iwamoto, Y., Sato, T., Hashimoto, S., Ogawa, T., Furuta, T., Abe, S., Kai, T., Matsuda, N., Hosoyamada, R., Niita, K. (2017). Benchmark study of the recent version of the PHITS code. Journal of Nuclear Science and Technology, 54(5), 617-635. doi:10.1080/00223131.2017.1297742
  • Ješkovský, M., Javorník, A., Breier, R., Slučiak, J., & Povinec, P. P. (2019). Experimental and Monte Carlo determination of HPGe detector efficiency. Journal of Radioanalytical and Nuclear Chemistry, 322(3), 1863-1869. doi:10.1007/s10967-019-06856-4
  • Kroese, D. P., & Rubinstein, R. Y. (2012). Monte Carlo methods. Wiley Interdisciplinary Reviews: Computational Statistics, 4(1), 48-58. doi:10.1002/wics.194
  • Lépy, M. C., Thiam, C., Anagnostakis, M., Galea, R., Gurau, D., Hurtado, S., Karfopoulos, K., Liang, J., Liu, H., Luca, A., Mitsios, I., Potiriadis, C., Savva, M. I., Thanh, T. T., Thomas, V., Townson, R. W., Vasilopoulou, T., & Zhang, M. (2019). A benchmark for Monte Carlo simulation in gamma-ray spectrometry. Applied Radiation and Isotopes, 154, 108850. doi:10.1016/j.apradiso.2019.108850
  • Mrdja, D., Bikit, K., Forkapic, S., Bikit, I., Slivka, J., & Hansman, J. (2018). Improvement of in-situ gamma spectrometry methods by Monte-Carlo simulations. Journal of Environmental Radioactivity, 188, 23-29. doi:10.1016/j.jenvrad.2017.11.005
  • Ordóñez, J., Gallardo, S., Ortiz, J., Sáez-Muñoz, M., & Martorell, S. (2019). Intercomparison of full energy peak efficiency curves for an HPGe detector using MCNP6 and GEANT4. Radiation Physics and Chemistry, 155, 248-251. doi:10.1016/j.radphyschem.2018.06.049
  • Sato, T., Iwamoto, Y., Hashimoto, S., Ogawa, T., Furuta, T., Abe, S., Kai, T., Tsai, P.-E., Matsuda, N., Iwase, H., Shigyo, N., Sihver, L., & Niita, K. (2018). Features of Particle and Heavy Ion Transport code System (PHITS) version 3.02. Journal of Nuclear Science and Technology, 55(6), 684-690. doi:10.1080/00223131.2017.1419890
  • Sima, O. (2012). Efficiency Calculation of Gamma Detectors by Monte Carlo Methods. Encyclopedia of Analytical Chemistry. doi:10.1002/9780470027318.a9142
  • Subercaze, A., Sauzedde, T., Domergue, C., Destouches, C., Philibert, H., Fausser, C., Thiollay, N., Gregoire, G., & Zoia, A. (2022). Effect of the geometrical parameters of an HPGe detector on efficiency calculations using Monte Carlo methods. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 1039, 167096. doi:10.1016/j.nima.2022.167096
  • Uyar, E., & Bölükdemir, M. H. (2022). Characterisation of two p-type HPGe detectors by measurements and Monte Carlo simulations. Measurement, 204, 112092. doi:10.1016/j.measurement.2022.112092
  • Vidmar, T., Kanisch, G., & Vidmar, G. (2011). Calculation of true coincidence summing corrections for extended sources with EFFTRAN. Applied Radiation and Isotopes, 69(6), 908-911. doi:10.1016/j.apradiso.2011.02.042
  • Yoon, E. T., Kang, M. Y., Kim, I. J., Sun, G. M., & Choi, H.-D. (2020). Coincidence summing correction for a voluminous 152Eu source. Nuclear Engineering and Technology, 52(6), 1266-1270. doi:10.1016/j.net.2019.11.015

Comparison of the Number of Particle History for Monte Carlo Codes in Gamma-Ray Spectroscopy

Year 2023, , 176 - 183, 27.06.2023
https://doi.org/10.54287/gujsa.1276486

Abstract

Monte Carlo is a numerical computation algorithm that is widely used in many fields of science and is used to obtain numerical results with a large number of repeated random samplings. Radiation transport with Monte Carlo simulation continues to increase its popularity in the fields of radiation measurement. The high accuracy and precision measurement of radionuclide activity amounts in gamma-ray spectrometry depends on the efficiency calibration of the detector. Efficiency calibration is carried out in two ways, using certified reference materials, by experimental method or Monte Carlo simulation method. The experimental method is expensive, procedurally complex and time-consuming due to the supply of reference material. The use of the Monte Carlo technique in a reliable way without the need for a standard radioactive source in determining the detector efficiency is becoming common. The most critical step for accurate and precise results in getting the response of a detector with the Monte Carlo method is modeling the detector with its realistic dimensions. Another parameter as important as detector modeling is the number of histories in the simulation code examined in this study. The effect of the number of histories on efficiency was examined in detail using PHITS, GESPECOR and DETEFF Monte Carlo simulation codes. Since there is no definite number about this effect, which is important for obtaining meaningful and realistic results, the change in the efficiency value was examined by increasing the number of stories from 105 to 108. The results obtained in this work showed that at least 107 particle numbers should be used in all three programs where the uncertainty is below 1%. If the existing facilities are sufficient, it can be increased to 108s in case of having a more equipped and fast computer. However, going higher than this value does not make any sense as seen from the study.

References

  • Azli, T., & Chaoui, Z. E.-A. (2015). Performance revaluation of a N-type coaxial HPGe detector with front edges crystal using MCNPX. Applied Radiation and Isotopes, 97, 106-112. doi:10.1016/j.apradiso.2014.12.027
  • Cebastien Joel, G. S., Maurice, N. M., Eric Jilbert, N. M., Ousmanou, M., & David, S. (2018). Monte Carlo method for gamma spectrometry based on GEANT4 toolkit: Efficiency calibration of BE6530 detector. Journal of Environmental Radioactivity, 189, 109-119. doi:10.1016/j.jenvrad.2018.03.015
  • Díaz, N. C., & Vargas, M. J. (2010). Improving the trade-off between simulation time and accuracy in efficiency calibrations with the code DETEFF. Applied Radiation and Isotopes, 68(7-8), 1413-1417. doi:10.1016/j.apradiso.2009.11.021
  • Iwamoto, Y., Sato, T., Hashimoto, S., Ogawa, T., Furuta, T., Abe, S., Kai, T., Matsuda, N., Hosoyamada, R., Niita, K. (2017). Benchmark study of the recent version of the PHITS code. Journal of Nuclear Science and Technology, 54(5), 617-635. doi:10.1080/00223131.2017.1297742
  • Ješkovský, M., Javorník, A., Breier, R., Slučiak, J., & Povinec, P. P. (2019). Experimental and Monte Carlo determination of HPGe detector efficiency. Journal of Radioanalytical and Nuclear Chemistry, 322(3), 1863-1869. doi:10.1007/s10967-019-06856-4
  • Kroese, D. P., & Rubinstein, R. Y. (2012). Monte Carlo methods. Wiley Interdisciplinary Reviews: Computational Statistics, 4(1), 48-58. doi:10.1002/wics.194
  • Lépy, M. C., Thiam, C., Anagnostakis, M., Galea, R., Gurau, D., Hurtado, S., Karfopoulos, K., Liang, J., Liu, H., Luca, A., Mitsios, I., Potiriadis, C., Savva, M. I., Thanh, T. T., Thomas, V., Townson, R. W., Vasilopoulou, T., & Zhang, M. (2019). A benchmark for Monte Carlo simulation in gamma-ray spectrometry. Applied Radiation and Isotopes, 154, 108850. doi:10.1016/j.apradiso.2019.108850
  • Mrdja, D., Bikit, K., Forkapic, S., Bikit, I., Slivka, J., & Hansman, J. (2018). Improvement of in-situ gamma spectrometry methods by Monte-Carlo simulations. Journal of Environmental Radioactivity, 188, 23-29. doi:10.1016/j.jenvrad.2017.11.005
  • Ordóñez, J., Gallardo, S., Ortiz, J., Sáez-Muñoz, M., & Martorell, S. (2019). Intercomparison of full energy peak efficiency curves for an HPGe detector using MCNP6 and GEANT4. Radiation Physics and Chemistry, 155, 248-251. doi:10.1016/j.radphyschem.2018.06.049
  • Sato, T., Iwamoto, Y., Hashimoto, S., Ogawa, T., Furuta, T., Abe, S., Kai, T., Tsai, P.-E., Matsuda, N., Iwase, H., Shigyo, N., Sihver, L., & Niita, K. (2018). Features of Particle and Heavy Ion Transport code System (PHITS) version 3.02. Journal of Nuclear Science and Technology, 55(6), 684-690. doi:10.1080/00223131.2017.1419890
  • Sima, O. (2012). Efficiency Calculation of Gamma Detectors by Monte Carlo Methods. Encyclopedia of Analytical Chemistry. doi:10.1002/9780470027318.a9142
  • Subercaze, A., Sauzedde, T., Domergue, C., Destouches, C., Philibert, H., Fausser, C., Thiollay, N., Gregoire, G., & Zoia, A. (2022). Effect of the geometrical parameters of an HPGe detector on efficiency calculations using Monte Carlo methods. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 1039, 167096. doi:10.1016/j.nima.2022.167096
  • Uyar, E., & Bölükdemir, M. H. (2022). Characterisation of two p-type HPGe detectors by measurements and Monte Carlo simulations. Measurement, 204, 112092. doi:10.1016/j.measurement.2022.112092
  • Vidmar, T., Kanisch, G., & Vidmar, G. (2011). Calculation of true coincidence summing corrections for extended sources with EFFTRAN. Applied Radiation and Isotopes, 69(6), 908-911. doi:10.1016/j.apradiso.2011.02.042
  • Yoon, E. T., Kang, M. Y., Kim, I. J., Sun, G. M., & Choi, H.-D. (2020). Coincidence summing correction for a voluminous 152Eu source. Nuclear Engineering and Technology, 52(6), 1266-1270. doi:10.1016/j.net.2019.11.015
There are 15 citations in total.

Details

Primary Language English
Subjects Nuclear Physics
Journal Section Physics
Authors

Esra Uyar 0000-0001-7585-9635

Zeynep Aybüke Günekbay 0009-0000-4049-1391

Early Pub Date June 20, 2023
Publication Date June 27, 2023
Submission Date April 3, 2023
Published in Issue Year 2023

Cite

APA Uyar, E., & Günekbay, Z. A. (2023). Comparison of the Number of Particle History for Monte Carlo Codes in Gamma-Ray Spectroscopy. Gazi University Journal of Science Part A: Engineering and Innovation, 10(2), 176-183. https://doi.org/10.54287/gujsa.1276486